Harmony search algorithm's parameter tuning for traveling salesman problem

This paper proposes statistical methods to find the parameter setting of an artificial intelligence technique, harmony search (HS) algorithm. The problem at hand is the travelling salesman problem (TSP) which is an NP-complete problem. Hence, a metaheuristic approach can give the near optimal soluti...

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Bibliographic Details
Published in:2017 International Conference on Robotics and Automation Sciences (ICRAS) pp. 199 - 203
Main Authors: Tongchan, Tanapat, Pomsing, Choosak, Tonglim, Tongtang
Format: Conference Proceeding
Language:English
Published: IEEE 01.08.2017
Subjects:
Decoding
Encoding
harmony search algorithm
Music
parameter setting
Search problems
Statistical analysis
statistical methods
traveling salesman problem
Traveling salesman problems
Urban areas
ISBN:1538639947, 9781538639948
Online Access:Get full text
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Summary:This paper proposes statistical methods to find the parameter setting of an artificial intelligence technique, harmony search (HS) algorithm. The problem at hand is the travelling salesman problem (TSP) which is an NP-complete problem. Hence, a metaheuristic approach can give the near optimal solution in reasonable amount of computational time. The study makes use of the conventional HS to solve three benchmark problem sets in literature. The encoding and decoding schemes are presented. Then, the general full factorial design is used to find the HS' parameter setting. The analysis shows that HMCR and iteration number are significant. In addition, the appropriate setting of HMCR is 0.3 and iteration number is 5000.
ISBN:1538639947
9781538639948
DOI:10.1109/ICRAS.2017.8071944